import math
x = [[1,0.1,0.6,1.1],
     [1,0.2,0.7,1.2],
     [1,0.3,0.8,1.3],
     [1,0.4,0.9,1.4],
     [1,0.5,1.,1.5]]
theta = [-2,-1,1,2]
y = [1,0,1,0,1]

def sigmoid(a):
    a *= -1
    return 1/(1+(math.exp(a)))

def get_predictions(x,theta):
    answers = []
    for i in range(len(x)):
        temp = 0
        for j in range(len(theta)):
            print(x[i][j], theta[j])
            thetax = x[i][j]*theta[j]
            temp += thetax
        temp = sigmoid(temp)
        answers.append(temp)

    return answers

def cost(y, pred):
    total_cost = 0
    for i in range(len(y)):
        cost_1 = -(y[i])*math.log(pred[i])
        cost_2 = (1-y[i])*math.log(1-pred[i])
        total_cost += cost_1-cost_2
    total_cost = (1/len(y))*total_cost

    return total_cost

new = get_predictions(x, theta)
print(new)
t_cost = cost(y, new)
print(t_cost)